CN117549304A - Digital twinning-based robot tunnel blasting pre-detection control method and system - Google Patents
Digital twinning-based robot tunnel blasting pre-detection control method and system Download PDFInfo
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- CN117549304A CN117549304A CN202311661412.5A CN202311661412A CN117549304A CN 117549304 A CN117549304 A CN 117549304A CN 202311661412 A CN202311661412 A CN 202311661412A CN 117549304 A CN117549304 A CN 117549304A
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- 238000001514 detection method Methods 0.000 title claims abstract description 74
- 238000005422 blasting Methods 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000004458 analytical method Methods 0.000 claims abstract description 62
- 239000013598 vector Substances 0.000 claims description 18
- 238000010276 construction Methods 0.000 claims description 12
- 238000004891 communication Methods 0.000 claims description 8
- 230000007613 environmental effect Effects 0.000 claims description 7
- 238000012795 verification Methods 0.000 claims description 6
- 238000013461 design Methods 0.000 abstract description 11
- 238000000605 extraction Methods 0.000 abstract description 7
- 239000011435 rock Substances 0.000 description 12
- 238000009412 basement excavation Methods 0.000 description 11
- 230000002159 abnormal effect Effects 0.000 description 4
- 238000005336 cracking Methods 0.000 description 3
- 230000005856 abnormality Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000002360 explosive Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 238000005553 drilling Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 239000002893 slag Substances 0.000 description 1
- 238000012876 topography Methods 0.000 description 1
Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J11/00—Manipulators not otherwise provided for
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
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- Mechanical Engineering (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention provides a digital twinning-based robot tunnel blasting pre-detection control method and a digital twinning-based robot tunnel blasting pre-detection control system, wherein the method comprises the following steps: after the tunnel is subjected to blasting operation, controlling the robot to enter the tunnel; controlling a robot to scan the environment in the tunnel to acquire pre-detection information; based on the pre-detection information, carrying out safety analysis in the tunnel to obtain an analysis result; based on the pre-detection information and the analysis result, a digital twin model of the tunnel is built; and visually outputting the digital twin model. According to the invention, the robot is controlled to complete acquisition, extraction and analysis of geological information of the excavated surface after tunnel blasting operation, a digital twin model of the tunnel is built, and a manager can carry out dynamic support design by checking the digital twin model, so that the acquisition, extraction, analysis and design of the geological information of the excavated surface are completed in a short time, the safety of tunnel engineering is greatly improved, and meanwhile, the system is more intelligent.
Description
Technical Field
The invention relates to the technical field of tunnel engineering, in particular to a digital twinning-based robot tunnel blasting pre-detection control method and system.
Background
The tunnel engineering has the characteristics of large investment, long construction period, more construction projects, complex construction technology, more unpredictable risk factors, large influence on social environment and the like, so the tunnel engineering is a high-risk construction engineering. Compared with general engineering, tunnel engineering has high multi-dimensional uncertainties, and the uncertainties affect various links of tunnel engineering construction. Due to the limitations of the complex geological environment, lack of basic information, additional investigation means and the like, the geological condition in construction cannot be completely mastered before excavation, and the original design scheme must be necessarily adjusted and corrected through the specific geological condition disclosed in the excavation process. In the tunnel construction process of the drilling and blasting method, the excavation surface is exposed after blasting slag discharge, and only about 1 hour is needed from the beginning of supporting construction. To achieve a true dynamic support design in each construction cycle, the excavation face geological information acquisition, extraction, analysis and design are required to be completed within 1 hour. This is almost impossible to accomplish with the manual acquisition, discrimination and design based technology architecture in existing survey design specifications. Thus, a solution is needed.
Disclosure of Invention
The invention aims to provide a digital twin-based control method for tunnel blasting pretreatment of a robot, which is used for controlling the robot to complete acquisition, extraction and analysis of geological information of an excavated surface after tunnel blasting operation, building a digital twin model of the tunnel, and enabling a manager to carry out dynamic support design by checking the digital twin model, so that the acquisition, extraction, analysis and design of the geological information of the excavated surface are completed in a short time, the safety of tunnel engineering is greatly improved, and meanwhile, the method is more intelligent.
The embodiment of the invention provides a digital twinning-based robot tunnel blasting pre-detection control method, which comprises the following steps:
after the tunnel is subjected to blasting operation, controlling the robot to enter the tunnel;
controlling a robot to scan the environment in the tunnel to acquire pre-detection information;
based on the pre-detection information, carrying out safety analysis in the tunnel to obtain an analysis result;
based on the pre-detection information and the analysis result, a digital twin model of the tunnel is built;
and visually outputting the digital twin model.
Preferably, the controlling the robot to scan the environment in the tunnel to obtain the pre-detection information includes:
calling a preset internal map corresponding to the tunnel;
determining a plurality of key scan locations from within the internal map;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information. Preferably, determining a plurality of key scan locations from within the internal map comprises:
calling a preset first search request library;
extracting a first search requirement from a search requirement library;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel;
extracting features of the operation history and the internal map to obtain a plurality of information features;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the second search requirement comprises:
the tunnel security event is related to each information feature;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer.
Preferably, planning a scan route of the robot within the interior map based on the plurality of key scan positions includes:
determining a plurality of residence positions in the internal map based on the residence position determining conditions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius;
the key scanning positions in the target range associated with different residence positions are mutually different;
the target range associated with all the residence positions contains all the key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range;
the residence position falls into a preset communication range corresponding to the tunnel.
Preferably, based on the pre-detection information, safety analysis is performed in the tunnel to obtain an analysis result, including:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base;
generating a fifth search requirement based on the scanning knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library;
expanding the scanning command history on a preset time axis to obtain a plurality of history items;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea.
The embodiment of the invention provides a digital twinning-based robot tunnel blasting pre-detection control system, which comprises the following components:
the first control module is used for controlling the robot to enter the tunnel after the tunnel performs blasting operation;
the second control module is used for controlling the robot to scan the environment in the tunnel and acquiring pre-detection information;
the analysis module is used for carrying out safety analysis on the tunnel based on the pre-detection information to obtain an analysis result;
the construction module is used for constructing a digital twin model of the tunnel based on the pre-detection information and the analysis result;
and the output module is used for visually outputting the digital twin model.
Preferably, the second control module controls the robot to scan the environment in the tunnel to obtain the pre-detection information, including:
calling a preset internal map corresponding to the tunnel;
determining a plurality of key scan locations from within the internal map;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information.
Preferably, the second control module determines a plurality of key scan locations from within the internal map, comprising:
calling a preset first search request library;
extracting a first search requirement from a search requirement library;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel;
extracting features of the operation history and the internal map to obtain a plurality of information features;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the second search requirement comprises:
the tunnel security event is related to each information feature;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer.
Preferably, the second control module plans a scan route of the robot within the interior map based on the plurality of key scan positions, including:
determining a plurality of residence positions in the internal map based on the residence position determining conditions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius;
the key scanning positions in the target range associated with different residence positions are mutually different;
the target range associated with all the residence positions contains all the key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range;
the residence position falls into a preset communication range corresponding to the tunnel.
Preferably, the analysis module performs security analysis on the tunnel based on the pre-detection information to obtain an analysis result, including:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base;
generating a fifth search requirement based on the scanning knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library;
expanding the scanning command history on a preset time axis to obtain a plurality of history items;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a digital twinning-based control method for blasting and pre-probing a robot tunnel in an embodiment of the invention;
fig. 2 is a schematic diagram of a digital twinning-based robot tunnel blasting pretreatment control system in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a digital twinning-based robot tunnel blasting pre-detection control method, which is shown in fig. 1 and comprises the following steps:
step S1: after the tunnel is subjected to blasting operation, controlling the robot to enter the tunnel;
step S2: controlling a robot to scan the environment in the tunnel to acquire pre-detection information;
step S3: based on the pre-detection information, carrying out safety analysis in the tunnel to obtain an analysis result;
step S4: based on the pre-detection information and the analysis result, a digital twin model of the tunnel is built;
step S5: and visually outputting the digital twin model.
In this embodiment, the robot is driven by a crawler, equipped with a millimeter wave radar, a camera, a power supply, a communication device, and the like; when the robot is controlled to scan the environment in the tunnel, the millimeter wave radar is controlled to scan the tunnel in three dimensions, the camera is controlled to shoot images in the tunnel, and the three-dimensional scanning information and the shot images are used as pre-detection information; when safety analysis is carried out, determining the stability of surrounding rock in a tunnel, a tunnel deformation area and the like based on the pre-detection information; constructing a digital twin model of the tunnel based on the pre-detection information and the analysis result, wherein the digital twin model restores the scene in the tunnel one by one, and the pre-detection information and the analysis result are expressed in the digital twin model; and visually outputting the digital twin model for a manager to check.
According to the control robot, the excavation face geological information acquisition, extraction and analysis are completed after the tunnel blasting operation, the digital twin model of the tunnel is built, and the manager can conduct dynamic support design through checking the digital twin model, so that the excavation face geological information acquisition, extraction, analysis and design are completed in a short time, the safety of tunnel engineering is greatly improved, and meanwhile, the control robot is more intelligent.
In one embodiment, controlling the robot to perform environmental scanning in the tunnel to obtain the pre-detection information includes:
calling a preset internal map corresponding to the tunnel; the internal map is a three-dimensional map in the tunnel;
determining a plurality of key scan locations from within the internal map; the key scanning position is a position in the tunnel where the robot is required to perform environmental scanning;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information.
In one embodiment, determining a plurality of key scan locations from within an internal map includes:
calling a preset first search request library;
extracting a first search requirement from a search requirement library; the first search requirement is a requirement for searching out a position of a foundation in a tunnel, where environmental scanning is required, for example: searching out the position of the blasting area [ the position of the blasting area needs to be subjected to environment scanning, determining whether surrounding rocks around the blasting area are stable ] and the like;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel; the job history includes: blasting history [ blasting region position, blasting explosive type, etc. ], excavation history [ excavation region position, excavation depth, etc. ], etc.;
extracting features of the operation history and the internal map to obtain a plurality of information features; the information features include: historical blasting area position, historical blasting explosive type, historical excavation area position, historical excavation depth, tunnel topography, rock stratum type and the like;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement; wherein the second search requirement comprises: the tunnel security event is related to each information feature; the tunnel security event is a large number of events of surrounding rock abnormality scanned by a robot in a tunnel in history, and the occurrence site of the tunnel security event can be a current tunnel, other tunnels and the like; through the limitation of the second search requirement, the tunnel security event is related to each information feature, so that the tunnel security event is more suitable for determining a plurality of key scanning positions in the current tunnel, and the determination accuracy is improved;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics; the event features include: the information of the included angle between the trend of the scanned surrounding rock and the axis of the tunnel, the information of the inclination angle of the rock stratum and the like when the surrounding rock in the tunnel is abnormal;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer. M can be set in advance by the skilled person; the feature types include: included angles between the trend of surrounding rock and the axis of the tunnel, the inclination angle of the rock stratum and the like; the feature weight represents the degree to which the event feature under the feature type needs to be related by the tunnel security event, and can be set in advance by a technician according to actual requirements; by setting the third search requirement, the searched key scanning position can be more comprehensive, and the system applicability is improved.
In one embodiment, planning a scan route of a robot within an interior map based on a plurality of key scan locations includes:
determining a plurality of residence positions in the internal map based on the residence position determining conditions; when the robot arrives in the tunnel, the robot stays at the standing position, and environmental scanning is performed on the peripheral key scanning positions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius; n is a positive integer which can be set in advance by a technician; the radius length may be, for example: 20 meters; setting the standing position determining condition can enable the robot to stay at the standing position after reaching the tunnel, and performing environment scanning on the key scanning position in the target range;
the key scanning positions in the target range associated with different residence positions are mutually different; the setting of the standing position determining condition can avoid the robot from carrying out repeated environment scanning on the same key scanning position;
the target range associated with all the residence positions contains all the key scanning positions; the setting of the standing position determining condition can ensure that the robot can perform environment scanning on all key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range; the angle threshold may be, for example: 75 degrees; by setting the standing position determining condition, when the robot stays at one standing position to perform environment scanning on the key scanning position in the target range, the scanning direction does not need to be switched at a large angle, the environment scanning efficiency of the robot is improved, and the environment scanning time is shortened;
the residence position falls into a preset communication range corresponding to the tunnel. The communication range is a coverage range in which the tunnel can communicate with the outside; by setting the standing position determining condition, the robot can send scanning information to the outside and be controlled remotely when staying at one standing position.
In one embodiment, based on the pre-detection information, performing security analysis on the tunnel to obtain an analysis result, including:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library; the fourth search requirement is to search out the event of the underlying tunnel anomaly, such as: searching out surrounding rock cracking situations and the like;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base; the scan knowledge indicates what pre-probe information represents a tunnel anomaly, such as: the scanning knowledge is that the length of the surrounding rock crack is 30cm, and the width of the cracking crack is 3cm;
generating a fifth search requirement based on the scanning knowledge; the fifth search requirement includes: the second tunnel security event is related to the scan knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result; such as: searching that the pre-detection information contains 'the length of a surrounding rock crack is 30cm and the width of a cracking gap is 3 cm', and taking the pre-detection information as a second tunnel security event and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library; the scanning command history is a record of environmental scanning control of a robot entering a tunnel by a manager in history;
expanding the scanning command history on a preset time axis to obtain a plurality of history items; when the method is used for expanding, the information is represented on a time axis based on the generation time of each piece of information in the scanning command history, so that a history item is obtained;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base; when the history item accords with the history item condition, the history item of the description object can indicate what kind of pre-detection information represents tunnel abnormality, so that knowledge to be put in storage is determined, and the knowledge is stored in a scanning knowledge base to update the scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment; the first time range may be, for example: 30 seconds; when other history items represent that the robot is subjected to multiple adjustment of the scanning angle, the other history items are records of multiple environmental scanning angle adjustment of the robot; when other history items in a first time range preset in front of the history item represent that the robot is adjusted by a plurality of times of scanning angles, if the content type of the history item is the robot scanning data, the condition that a manager remotely controls the robot to perform environment scanning is indicated, and tunnel abnormal data is scanned after the environment scanning angles are adjusted by a plurality of times;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea. The second time range may be, for example: 15 seconds; other history items characterize semantics of speech given when verifying the controller's ideas for the manager to control the robot, such as: the sequence is "abnormal here", "opposite bar, indeed abnormal". The history item conditions are set to screen the history item, so that the updating accuracy and updating quality of the scanning knowledge base are improved, and the capability of the scanning knowledge base for generating fifth search requirements is indirectly improved.
The embodiment of the invention provides a digital twinning-based robot tunnel blasting pre-detection control system, which is shown in fig. 2 and comprises the following steps:
the first control module 1 is used for controlling the robot to enter the tunnel after the blasting operation is carried out on the tunnel;
the second control module 2 is used for controlling the robot to scan the environment in the tunnel and acquiring pre-detection information;
the analysis module 3 is used for carrying out safety analysis on the tunnel based on the pre-detection information to obtain an analysis result;
the construction module 4 is used for constructing a digital twin model of the tunnel based on the pre-detection information and the analysis result;
and the output module 5 is used for visually outputting the digital twin model.
The second control module 2 controls the robot to scan the environment in the tunnel to acquire the pre-detection information, and the method comprises the following steps:
calling a preset internal map corresponding to the tunnel;
determining a plurality of key scan locations from within the internal map;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information.
The second control module 2 determines a plurality of key scan locations from within the internal map, including:
calling a preset first search request library;
extracting a first search requirement from a search requirement library;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel;
extracting features of the operation history and the internal map to obtain a plurality of information features;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the second search requirement comprises:
the tunnel security event is related to each information feature;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer.
The second control module 2 plans a scan route of the robot within the interior map based on the plurality of key scan positions, including:
determining a plurality of residence positions in the internal map based on the residence position determining conditions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius;
the key scanning positions in the target range associated with different residence positions are mutually different;
the target range associated with all the residence positions contains all the key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range;
the residence position falls into a preset communication range corresponding to the tunnel.
The analysis module 3 performs security analysis on the tunnel based on the pre-detection information to obtain an analysis result, and includes:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base;
generating a fifth search requirement based on the scanning knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library;
expanding the scanning command history on a preset time axis to obtain a plurality of history items;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The digital twinning-based robot tunnel blasting pre-detection control method is characterized by comprising the following steps of:
after the tunnel is subjected to blasting operation, controlling the robot to enter the tunnel;
controlling a robot to scan the environment in the tunnel to acquire pre-detection information;
based on the pre-detection information, carrying out safety analysis in the tunnel to obtain an analysis result;
based on the pre-detection information and the analysis result, a digital twin model of the tunnel is built;
and visually outputting the digital twin model.
2. The method for controlling blasting pre-detection of a robot tunnel based on digital twinning as claimed in claim 1, wherein the method for controlling the robot to scan the environment in the tunnel to obtain the pre-detection information comprises the following steps:
calling a preset internal map corresponding to the tunnel;
determining a plurality of key scan locations from within the internal map;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information.
3. The digital twinning-based robotic tunnel blasting pre-detection control method of claim 2, wherein determining a plurality of key scan locations from within an internal map comprises:
calling a preset first search request library;
extracting a first search requirement from a search requirement library;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel;
extracting features of the operation history and the internal map to obtain a plurality of information features;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the second search requirement comprises:
the tunnel security event is related to each information feature;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer.
4. The digital twinning-based control method for robot tunnel blasting pretreatment as claimed in claim 2, wherein the planning of the scanning route of the robot in the internal map based on the plurality of key scanning positions comprises:
determining a plurality of residence positions in the internal map based on the residence position determining conditions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius;
the key scanning positions in the target range associated with different residence positions are mutually different;
the target range associated with all the residence positions contains all the key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range;
the residence position falls into a preset communication range corresponding to the tunnel.
5. The method for controlling blasting pre-detection of a robot tunnel based on digital twinning as claimed in claim 1, wherein the safety analysis is performed in the tunnel based on the pre-detection information to obtain the analysis result, comprising:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base;
generating a fifth search requirement based on the scanning knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library;
expanding the scanning command history on a preset time axis to obtain a plurality of history items;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea.
6. Digital twinning-based robot tunnel blasting pre-detection control system is characterized by comprising:
the first control module is used for controlling the robot to enter the tunnel after the tunnel performs blasting operation;
the second control module is used for controlling the robot to scan the environment in the tunnel and acquiring pre-detection information;
the analysis module is used for carrying out safety analysis on the tunnel based on the pre-detection information to obtain an analysis result;
the construction module is used for constructing a digital twin model of the tunnel based on the pre-detection information and the analysis result;
and the output module is used for visually outputting the digital twin model.
7. The digital twinning-based robot tunnel blasting pre-detection control system according to claim 6, wherein the second control module controls the robot to perform environmental scanning in the tunnel to obtain pre-detection information, and the method comprises the following steps:
calling a preset internal map corresponding to the tunnel;
determining a plurality of key scan locations from within the internal map;
planning a scanning route of the robot in the internal map based on the plurality of key scanning positions;
based on the scanning route, controlling the robot to scan the environment in the tunnel to acquire the pre-detection information.
8. The digital twinning-based robotic tunnel blasting foredetection control system of claim 7, wherein the second control module determines a plurality of key scan positions from within the internal map, comprising:
calling a preset first search request library;
extracting a first search requirement from a search requirement library;
searching for a key scanning location within the internal map based on the first search requirement;
and/or the number of the groups of groups,
acquiring the operation history of a tunnel;
extracting features of the operation history and the internal map to obtain a plurality of information features;
generating a second search requirement based on the plurality of information features;
searching for a tunnel security event through a preset searching source based on a second searching requirement;
extracting characteristics of the tunnel security event to obtain a plurality of event characteristics;
generating a third search requirement based on the plurality of event features;
searching for a key scanning location within the internal map based on the third search requirement;
wherein the second search requirement comprises:
the tunnel security event is related to each information feature;
wherein the third search requirement includes:
the tunnel security event is associated with each event feature in the target feature set; the target feature set comprises at least M event features, and the sum of preset feature weights corresponding to feature types of all event features in the target feature set is larger than or equal to a preset weight and a threshold value; m is a positive integer.
9. The digital twinning-based robotic tunnel blasting pre-search control system of claim 7, wherein the second control module programs a scan path of the robot within the interior map based on a plurality of key scan locations, comprising:
determining a plurality of residence positions in the internal map based on the residence position determining conditions;
planning a shortest route of the robot to each residence in turn in the internal map, and taking the shortest route as a scanning route;
wherein the residence position determining conditions include:
at least N key scanning positions exist in the target range; the target range is associated with one residence position, and is a spherical range drawn by taking the associated residence position as a sphere center and the preset radius length as a sphere radius;
the key scanning positions in the target range associated with different residence positions are mutually different;
the target range associated with all the residence positions contains all the key scanning positions;
the maximum vector included angle between every two direction vectors is smaller than or equal to a preset included angle threshold value; the direction vector is constructed based on the sphere center and the target direction in the same target range; the target direction is a straight line direction from the sphere center to a key scanning position in the target range;
the residence position falls into a preset communication range corresponding to the tunnel.
10. The digital twinning-based robot tunnel blasting pre-detection control system according to claim 6, wherein the analysis module performs security analysis on the tunnel based on the pre-detection information to obtain an analysis result, and the method comprises:
scheduling a preset second search request library;
extracting a fourth search requirement from the second search requirement library;
searching a first tunnel security event from the pre-detection information based on a fourth search requirement, and taking the first tunnel security event as an analysis result;
and/or the number of the groups of groups,
updating a preset scanning knowledge base;
extracting scanning knowledge from a scanning knowledge base;
generating a fifth search requirement based on the scanning knowledge;
searching a second tunnel security event from the pre-detection information based on a fifth search requirement, and taking the second tunnel security event as an analysis result;
wherein updating the preset scanning knowledge base comprises:
calling a preset scanning command history library;
extracting a scanning command history from a scanning command history library;
expanding the scanning command history on a preset time axis to obtain a plurality of history items;
determining knowledge to be put in storage based on history items conforming to the history item conditions, and storing the knowledge into a scanning knowledge base;
wherein the history item condition includes:
the content type of the history item is robot scanning data, and other history items in a first time range preset in front of the history item on a time axis represent that the robot is subjected to multiple scanning angle adjustment;
or alternatively, the first and second heat exchangers may be,
the content type of the history item is robot scan data and other history items within a second time range preset before and after the history item on the time axis characterize the verification controller idea.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210366186A1 (en) * | 2019-09-06 | 2021-11-25 | Shandong University | Tbm-mounted virtual reconstruction system and method for surrounding rock structure of tunnel |
| CN114241720A (en) * | 2021-12-24 | 2022-03-25 | 北京市市政工程研究院 | Tunnel construction intelligent forecasting and early warning system and method based on digital twins |
| CN116012336A (en) * | 2023-01-09 | 2023-04-25 | 中国地质大学（北京） | Tunnel intelligent geological sketch and surrounding rock grade identification device and method |
| CN116381803A (en) * | 2023-03-17 | 2023-07-04 | 中铁二十局集团第五工程有限公司 | Comprehensive geophysical prospecting method for tunnel construction |
| CN116911115A (en) * | 2023-07-06 | 2023-10-20 | 华南理工大学 | Digital twin tunnel and intelligent construction method and system |
| CN116908214A (en) * | 2023-09-14 | 2023-10-20 | 中交路建交通科技有限公司 | Tunnel construction defect detection method and system based on digital twinning |
| CN117011759A (en) * | 2023-06-28 | 2023-11-07 | 西南交通大学 | Method and system for analyzing multi-element geological information of surrounding rock of tunnel face by drilling and blasting method |
-
2023
- 2023-12-06 CN CN202311661412.5A patent/CN117549304B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210366186A1 (en) * | 2019-09-06 | 2021-11-25 | Shandong University | Tbm-mounted virtual reconstruction system and method for surrounding rock structure of tunnel |
| CN114241720A (en) * | 2021-12-24 | 2022-03-25 | 北京市市政工程研究院 | Tunnel construction intelligent forecasting and early warning system and method based on digital twins |
| CN116012336A (en) * | 2023-01-09 | 2023-04-25 | 中国地质大学（北京） | Tunnel intelligent geological sketch and surrounding rock grade identification device and method |
| CN116381803A (en) * | 2023-03-17 | 2023-07-04 | 中铁二十局集团第五工程有限公司 | Comprehensive geophysical prospecting method for tunnel construction |
| CN117011759A (en) * | 2023-06-28 | 2023-11-07 | 西南交通大学 | Method and system for analyzing multi-element geological information of surrounding rock of tunnel face by drilling and blasting method |
| CN116911115A (en) * | 2023-07-06 | 2023-10-20 | 华南理工大学 | Digital twin tunnel and intelligent construction method and system |
| CN116908214A (en) * | 2023-09-14 | 2023-10-20 | 中交路建交通科技有限公司 | Tunnel construction defect detection method and system based on digital twinning |
Non-Patent Citations (1)
| Title |
|---|
| 葛世荣;张帆;王世博;王忠宾;: "数字孪生智采工作面技术架构研究", 煤炭学报, no. 06, 15 June 2020 (2020-06-15), pages 23 - 34 * |
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